US Patent Issued to Maplebear on Jan. 28 for "Weakly supervised extraction of attributes from unstructured data to generate training data for machine learning models" (California, Texas Inventors)

ALEXANDRIA, Va., Jan. 29 -- United States Patent no. 12,210,591, issued on Jan. 28, was assigned to Maplebear Inc. (San Francisco).

"Weakly supervised extraction of attributes from unstructured data to generate training data for machine learning models" was invented by Shih-Ting Lin (Austin, Texas), Jonathan Newman (Menlo Park, Calif.), Min Xie (Santa Clara, Calif.) and Haixun Wang (Palo Alto, Calif.).

According to the abstract* released by the U.S. Patent & Trademark Office: "An online concierge system receives unstructured data describing items offered for purchase by various warehouses. To generate attributes for products from the unstructured data, the online concierge system extracts candidate values for attributes from the unstructu...